Efficient modeling of higher-order dependencies in networks: from algorithm to application for anomaly detection
Abstract
Complex systems, represented as dynamic networks, comprise of components that influence each other via direct and/or indirect interactions. Recent research has shown the importance of using Higher-Order Networks (HONs) for modeling and analyzing such complex systems, as the typical Markovian assumption in developing the First Order Network (FON) can be limiting. This higher-order network representation not only creates a more accurate...
Paper Details
Title
Efficient modeling of higher-order dependencies in networks: from algorithm to application for anomaly detection
Published Date
Jun 9, 2020
Journal
Volume
9
Issue
1
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